Excessively Volatile Stock Markets: Equilibrium Computation and Policy Analysis

This paper incorporates excess volatility in stock prices into a standard general equilibrium model and finds large welfare gains from stabilizing policies. Stock prices in this model aggregate information about fundamentals which is dispersed in the economy but also reflect excess volatility stemming from correlated distortions in beliefs. To solve the model, this paper develops a novel solution method for nonlinear models with dispersed information which can be applied to a large class of dynamic general equilibrium models. The innovation lies in a nonlinear change of variables which, when combined with perturbation methods, yields the nonlinear price function consistent with equilibrium expectation operators. The main positive result shows that dispersion of information allows arbitrarily small distortions in beliefs to generate large amounts of excess volatility and renders arbitrage infeasible. The government cannot observe whether a given stock price movement originates from information or noise. As a normative result, price stabilizing policies lead to a higher level of consumption: a fall in the risk premium lowers the marginal product of capital and raises the capital stock and production. History-dependent policies may improve the information content of prices and result in even higher welfare gains. JEL classification: C63, E44, E61, G18, H21 I am indebted to John Y. Campbell, Nicola Fuchs-Schündeln, Kenneth L. Judd, N. Gregory Mankiw, and Andrei Shleifer for many discussions and suggestions. I also thank George-Marios Angeletos, Robert Barro, Emmanuel Farhi, Tarek Hassan, David Laibson, and seminar participants at Harvard University, MIT, NYU Stern School of Business, the Federal Reserve Banks of Boston and of New York, Duke University, Carnegie-Mellon, Boston University, and the Bank for International Settlements for valuable comments. ∗Finance Department, New York University, Stern School of Business, e-mail: [email protected]